The paradigm of cancer treatment is changing as more treatments are administered in oral form. This shift is well illustrated by the current recommended treatment of chronic myeloid leukemia (CML). The 5-year survival rate for CML has doubled over the past two decade (31% to 66%) in large part due to the discovery of targeted drugs, specifically tyrosine kinase inhibitors (TKIs). In contrast to most cancer treatments that are administered by an infusion in a controlled setting, TKIs are oral agents that require daily doses, most likely for life. The individual with CML is responsible for administration of every dose of this life saving drug every day. Although essential, adherence to TKIs is difficult; about a third of CML patients are reported to be nonadherent. Effectiveness of TKI therapy is measured by cytogenetic and molecular response and achievement of complete response is prognostic for long term-survival. Adherence is associate with achievement of a complete molecular response and results in improved overall survival. So why are a third of individuals with CML nonadherent? Specific to CML, patients may miss TKIs due to distress from side effects and financial toxicity. Distressing side effects from TKIs that reduce adherence include fatigue, pain, gastrointestinal upset, swelling and skin rashes. Financial toxicity occurs due to the expense of the TKIs ($30,000- $138,000/year) in combination with increasing insurance co-pays and out of pocket (OOP) costs. For instance, Medicare Part D enrollees paid a mean OOP cost for TKI therapy of $8,503 in 2016. These high drug costs plus other OOP costs related to cancer care result in changes in lifestyle, missed medical appointments and missed doses of medication. To more fully understand adherence and the effects on clinical outcomes, we need to consider the intrapatient and interpatient variability of medication adherence. This study will follow a group of 120 individuals taking TKIs for 12 months, measuring adherence with an objective measure (Medication Event Monitoring System) along with monthly assessments of toxicity (side effects and financial). To understand the variability of long term adherence, we will use these data to determine subgroups of adherence patterns (or trajectories) over time using model-based cluster analysis. Then, using both quantitative and qualitative data, we will examine how different toxicities are associated with the different adherence patterns. Next we will examine the influence of TKI adherence patterns on cytogenetic and molecular response. Identifying differential patterns of adherence in individuals taking TKIs is important for identifying subgroups at the highest risk of nonadherence and will support the design of targeted interventions.